CN108462521B - Anti-interference realization method of self-adaptive array antenna - Google Patents
Anti-interference realization method of self-adaptive array antenna Download PDFInfo
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Abstract
The invention discloses an anti-interference realization method of a self-adaptive array antenna, aiming at providing an anti-interference method with small calculation amount, strong real-time performance and better anti-interference effect. The invention is realized by the following technical scheme: in a uniform circular array antenna with an antenna array element number of M, a data preprocessing module carries out N-order time domain tapping on M paths of digital signals to obtain continuous space-time two-dimensional snapshot data, and meanwhile, space-time two-dimensional guide vectors are obtained according to expected signal directions provided by an upper computer; the minimum variance distortionless response MVDR algorithm simplification realization module calculates a guide vector residual matrix by utilizing a space-time two-dimensional guide vector, and simultaneously performs space-time two-dimensional beam synthesis and space-time two-dimensional weight iteration according to a built-in beam synthesis module and a weight iteration module by combining space-time two-dimensional snapshot data; the array output module converts the digital signals after beam forming into analog signals through a digital-to-analog DA converter, and the analog signals are up-converted and output to the back-end processor through an up-conversion module.
Description
Technical Field
The invention relates to a signal processing realization method suitable for an adaptive array antenna anti-interference system, in particular to an adaptive array antenna anti-interference technology.
Background
The adaptive array antenna is an active antenna with an anti-interference function, and can be applied to the application fields of sonar, radar navigation, communication and the like. The adaptive array antenna structure is greatly different from a traditional passive antenna, and comprises three modules with different fields and different functions, namely a passive array surface, a radio frequency front end and signal processing. The antenna array arrangement and the self-adaptive signal processing are combined, the antenna adjustment parameters are automatically controlled through the array signal processing, the complex weighting is carried out on the input signals of each array element, the amplitude and the phase adjustment of the received signals are completed, the spatial filtering is realized, the main beam of an antenna directional diagram is aligned to the useful signal direction, the zero point points to the interference direction, the interference signals which have different spatial directions with the desired signals are restrained while the desired signals are enhanced, and the corresponding array gain is generated.
In the current anti-interference technology, the adaptive array antenna occupies a very important position, can dynamically track user signals, and automatically adjust the weighting coefficient of each array element according to the external signal environment, so that the main lobe of a beam directional diagram is aligned to the incoming direction of an expected signal, and the null or lower side lobe is aligned to the incoming direction of an interference signal, thereby achieving the effect of nulling the interference signal and effectively inhibiting the interference signal. The beam forming algorithm is one of the main problems in array antenna research, the performance of the adaptive beam former is reduced due to array covariance matrix estimation errors caused by limited sampling, the existence of coherent interference signals and the like, and the application of the adaptive beam former is limited to a great extent due to the high computational complexity of the existing algorithm. In general, the adaptive array antenna weight vector is calculated by an adaptive algorithm, and is the core of adaptive array processing. The solving weight vector is actually a multi-parameter optimization problem under a certain criterion, and the main criteria are a maximum signal-to-interference-and-noise ratio (MSINR) criterion, a Minimum Mean Square Error (MMSE) criterion and a Linear Constraint Minimum Variance (LCMV) criterion. In fact, ideally, these three criteria are equivalent, and the LCMV criterion is simpler and more efficient, and becomes the most common optimization criterion in engineering practice. Among them, the Power Inversion (PI) algorithm and the Minimum Variance Distortionless Response (MVDR) algorithm are most widely used.
The PI algorithm is to invert the power ratio of the satellite signal to the noise signal on the premise that the satellite signal strength is far lower than the noise signal strength. The mean square minimum of the difference between the reference signal and the array output is used as an objective function, and the weight vector of the array is adjusted according to the system error to enable the objective function to be minimum, so that the function of self-adaptive adjustment is achieved. The algorithm directly takes the signal received by a certain antenna unit as a reference signal, does not need to acquire information such as the incident direction and the characteristics of the signal in advance, and is relatively simple to realize. The PI algorithm can be realized through a least mean square error algorithm (LMS), the method is jointly proposed by Widrop and Hoff, belongs to one of random gradient algorithms, and has the remarkable characteristics of simple operation and easy realization. The Delayed LMS (DLMS) algorithm is more used in high-speed real-time signal processing, and the past error is used for updating the coefficient, so that the filter and the coefficient updating module can work simultaneously, and the parallelism of the system is greatly improved. The PI algorithm is based on the minimum output energy criterion, can self-adaptively adjust the direction diagram to enable the null to point to the arrival direction of the interference, has the advantages that satellite direction information is not needed, and has the defect that the attenuation of a received expected signal is possibly caused while the interference is suppressed.
The MVDR algorithm can minimize the array output power in the desired signal direction and maximize the signal-to-interference-and-noise ratio, and is an adaptive spatial spectrum estimation algorithm proposed by Capon. The method ensures that the weight values of all array elements are adjusted under the condition that the gain constraint of the direction of the expected signal is 1, so that the output power of the array antenna is minimum, the direction of the expected signal needs to be known, and the power intensity of the expected signal is not concerned. Under the condition that the expected signal direction is known, the anti-interference comprehensive performance of the MVDR algorithm is better than that of the PI algorithm, but the specific implementation is more complex. The MVDR algorithm adds a steering vector constraint of a desired signal, so that iterative computation is more complex, and a conventional implementation method can be as follows:
step 1: initializing a weighting coefficient w (0), iterating a step size mu, and calculating a guide vector a;
step 2: n is the number of iterations, and is taken to be 0,1,2,3 …
1) And (3) autocorrelation matrix calculation: r (n) ═ x (n) xH(n), x is the array input, H represents the conjugate transpose;
2) updating iteration parameters: λ (n) ═ μ aHa)-1(aHw(n)-2μaHR(n)w(n)-1)；
3) Updating the weighting coefficient: w (n +1) ═ w (n) — μ (2r (n) w (n) + λ (n) a), return to step 2;
and step 3: calculating array output y (n) w according to the array input and the obtained weightH(n) x (n), completing the beam synthesis.
Therefore, weight iteration and beam forming cannot be separated and can only be realized in series, meanwhile, matrix operation is more in the whole algorithm realization process, if the method is applied to an array antenna space-time two-dimensional combined anti-interference system, hardware resource consumption is increased in a multiple mode, and the technical defects of large calculation amount, poor instantaneity, poor anti-interference effect and difficulty in implementation in engineering application exist.
Disclosure of Invention
The invention aims to solve the technical problems of large calculation amount and poor real-time performance of the existing method, and provides an anti-interference method of a self-adaptive array antenna, which has the advantages of small calculation amount, good real-time performance, better anti-interference effect and easy engineering realization.
In order to solve the above technical problem, the present invention provides an anti-interference implementation method for an adaptive array antenna, which is characterized by comprising the following steps: in the uniform circular array antenna with M antenna array elements, the distance between the antenna array elements is set to be half wavelength of an expected signal; each array element receives expected signals and interference signals from different directions, and M paths of digital signals are obtained after amplification, down conversion and analog-to-digital (AD) sampling; the data preprocessing module carries out N-order time domain tapping on the M paths of digital signals to obtain continuous space-time two-dimensional snapshot data, and meanwhile, corresponding space-time two-dimensional guide vectors are obtained according to expected signal directions provided by an upper computer; the minimum variance distortionless response MVDR algorithm simplification realization module receives space-time two-dimensional snapshot data and space-time two-dimensional guide vectors corresponding to the space-time two-dimensional snapshot data, calculates a guide vector residual matrix, and then simultaneously performs space-time two-dimensional beam synthesis and space-time two-dimensional weight iteration according to a built-in beam synthesis module and a weight iteration module; the array output module converts the digital signals after beam forming into analog signals through a digital-to-analog DA converter, and the analog signals are up-converted and output to a rear-end processor through an up-conversion module.
Further, the minimum variance distortionless response MVDR algorithm simplification implementation method is as follows:
step 1: calculating a steering vector residual matrix:
A＝I-(aaH)/(aHa) wherein I is a unit matrix, a is a space-time two-dimensional steering vector, and H represents conjugate transpose operation;
step 2: the beam synthesis module calculates the space-time two-dimensional beam synthesis value of the adaptive array antenna in real time
y(n)＝wH(n) x (n), wherein x is space-time two-dimensional snapshot data, w is a space-time two-dimensional weight, n represents time,
n＝0,1,2…；
and step 3: the weight iteration module takes n as 0,1,2,3 … and initializes w (0) as a;
1) and (3) calculating a delay correlation matrix: b (n-D) ═ x (n-D) conj (y (n-D)), conj denotes conjugate calculation, and D denotes a delay unit.
2) And (3) iterative update calculation of the weight: w (n +1) ═ w (n) -2 μ AB (n-D), μ denotes the iteration step size.
Therefore, the beam synthesis can obtain y (n) and simultaneously obtain the weight required by the next iteration by using the delayed x (n-D) and y (n-D), the two processes of the beam synthesis and the weight iteration do not have the restriction relation in sequence, and the simplified realization algorithm can finish the beam synthesis and the weight iteration in parallel in the same time.
Compared with the prior art, the invention has the following beneficial effects:
the calculated amount is small, and the real-time performance is good. In the specific implementation of the invention, the initial value of the space-time two-dimensional weighting vector is the space-time two-dimensional guide vector of the expected signal, and simultaneously, the product of the guide vector and the weighting vector is always equal to 1 in the whole iteration process, so that a in the conventional MVDR implementation algorithmHw (n) -1 equals zero after reduction, a can be directly omittedHA calculation step of w (n); meanwhile, the simplified realization algorithm also introduces a delay unit D in the weight iteration updating process, so that the beam synthesis module and the weight iteration module are realized independently and parallelly without being carried out serially according to the conventional MVDR realization algorithm, and R (n-D) w (n-D) ═ x (n-D) x can be known through matrix operationH(n-D) w (n-D) ═ x (n-D) conj (y (n-D)), so the product of the autocorrelation matrix and the weighting vector which can be obtained only by carrying out three times of matrix multiplication operation originally can be obtained by directly multiplying the conjugate of the array input delay and the array output delay, on one hand, the multiplier resource is saved, the hardware calculation amount is reduced, the real-time property of system processing is improved, and the complexity of the system is reduced, on the other hand, the beam synthesis module and the weight iteration module can simultaneously carry out space-time two-dimensional beam synthesis and space-time two-dimensional weight iteration, the serial work in the same order as the conventional MVDR realization algorithm is not needed, the weight convergence speed is accelerated, and the system working frequency is improved.
The anti-interference effect is better. The invention sets the antenna array element spacing of the circular array antenna with the M antenna array elements as the half wavelength of the expected signal, so that each array element receives the expected signal and the interference signal from different directions, and M paths of input signals are obtained after amplification, down conversion and sampling; then, N-order delay processing is carried out on the M paths of input signals to obtain input data of M multiplied by N dimensions, a space-time two-dimensional guide vector is calculated according to the expected signal direction and is set as an initial value of space-time weight iteration; then, a delay strategy is adopted on the basis of an MVDR algorithm, so that a space-time two-dimensional beam synthesis module and a coefficient iteration updating module can work simultaneously, on one hand, instantaneous data and real-time weight are directly weighted to complete space-time two-dimensional beam synthesis, and on the other hand, the updating of weight coefficients is realized by utilizing the past instantaneous data; and finally, the space-time two-dimensional beam forming module converts the digital signals subjected to beam forming into analog signals, and the analog signals are output to a rear-end processor through an up-conversion module. The anti-interference characteristic of the circular array antenna array is verified through experiments, and the test result of the steady-state directional diagram of the system when interference signals exist at different angles is given. The butt joint test with the receiver shows that the self-adaptive antenna system can greatly improve the anti-interference capability of the receiver and is easy to upgrade the existing system.
The invention simplifies the conventional method through formula derivation, and simultaneously introduces the delay unit to realize high-speed parallel pipeline processing. The method is particularly suitable for an adaptive array antenna anti-interference processing system.
Drawings
The invention is further illustrated with reference to the following figures and examples.
Fig. 1 is a schematic diagram of an anti-interference process of an adaptive array antenna according to the present invention.
Fig. 2 is a schematic diagram of the spatial geometry of an adaptive array antenna model.
Fig. 3 is a block diagram of a space-time two-dimensional beamforming module.
In order to better understand the technical solutions, the technical solutions will be described in detail below with reference to the drawings and specific embodiments of the specification. In the preferred embodiment of the present invention described below, an adaptive array antenna interference rejection implementation is provided.
Detailed Description
See fig. 1. In this embodiment, the uniform circular array antenna is an array antenna with four array elements, the distance between each array element is half wavelength of an expected signal, each array element receives the expected signal and an interference signal from different directions, and four paths of digital input signals are obtained after amplification, down conversion and analog-to-digital (AD) sampling; then, the data preprocessing module carries out five-order time domain tapping on the four-path digital signals to obtain continuous space-time two-dimensional snapshot data, meanwhile, corresponding space-time two-dimensional guide vectors are obtained according to expected signal directions provided by an upper computer, and the space-time two-dimensional snapshot data and the corresponding space-time two-dimensional guide vectors are sent to the simplified MVDR algorithm implementation module; then after a minimum variance distortionless response MVDR algorithm simplification implementation module calculates a guide vector residual matrix, a delay strategy is adopted to enable a beam synthesis module and a coefficient iteration updating module to be mutually independent, under the drive of a hardware system clock, the beam synthesis module directly weights according to instantaneous snapshot data and real-time weight to implement space-time two-dimensional beam synthesis, and the weight iteration module utilizes past snapshot data and beam synthesis data to implement iteration updating of weight coefficients; and finally, the array output module converts the digital signals subjected to beam forming into analog signals through a DA module, and outputs the analog signals to a rear-end processor through an up-conversion module.
Furthermore, in the process of simplifying and realizing the minimum variance distortionless response MVDR algorithm, the product of the constrained space-time two-dimensional guide vector a and the space-time two-dimensional weighting vector w is always equal to 1, namely aHw (n) ═ 1, according to which the iteration parameter λ (n) ═ μ a at the moment n of the conventional implementation algorithm is simplifiedHa)-1(aHw(n)-2μaHR (n) w (n) -1) to obtain:
λ(n)＝(aHa)-1(2aHR(n)w(n))
then, the weight coefficient is substituted into a weight coefficient updating formula w (n +1) ═ w (n) - μ (2r (n) w (n)) + λ (n) a of a conventional algorithm, so as to obtain:
w(n+1)＝w(n)-2μ(I-(aaH)/(aHa))R(n)w(n)
calculating R (n) ═ x (n) x from the autocorrelation matrixH(n) obtaining:
w(n+1)＝w(n)-2μ(I-(aaH)/(aHa))x(n)xH(n)w(n)
while outputting data y (n) w due to array beamformingH(n) x (n), and the conjugate conj (y (n)) x of the beamforming output is known from the matrix operationH(n) w (n), a delay strategy is adopted for this purpose, a delay unit D is introduced, and the weight required by the next iteration can be obtained by using the delayed x (n-D) and y (n-D) while the beam synthesis is carried out to obtain y (n), so that the weight iteration and the beam synthesis of the conventional serial operation are independent from each other and can be realized in parallel. Therefore, the new weight iteration formula is:
w(n+1)＝w(n)-2μ(I-(aaH)/(aHa))x(n-D)conj(y(n-D))＝w(n)-2μAB(n-D)
wherein mu is iteration step length, and a residual matrix A of the guide vector is defined as I- (aa)H)/(aHa) The input/output delay correlation matrix B (n-D) ═ x (n-D) conj (y (n-D)).
The specific implementation steps are as follows:
the minimum variance distortionless response MVDR algorithm simplification realization module calculates a guide vector residual matrix A as I- (aa) according to a unit matrix I and a space-time two-dimensional guide vector a in a circular array antennaH)/(aHa)。
The space-time two-dimensional beam synthesis module calculates the output data y (n) w of the space-time two-dimensional beam synthesis of the adaptive array antenna in real time according to the instantaneous value of the space-time two-dimensional weighting vector w and the instantaneous value of the space-time two-dimensional snapshot data xH(n)x(n)。
The weight iteration module firstly calculates an input/output delay correlation matrix B (n-D) ═ x (n-D) conj (y (n-D)) according to the space-time two-dimensional snapshot data x and the beam synthesis output y; and combining the iteration step size mu, the weight A of the guide vector residual matrix and the weight at the moment n, and calculating the weight w (n +1) ═ w (n) -2 mu AB (n-D) at the moment n + 1.
See fig. 2. A three-dimensional space rectangular coordinate system is established by an array antenna array surface according to XYZ axes, the azimuth angle of an incident signal is defined to be phi, the pitch angle is defined to be theta, solid points in the diagram represent antenna array elements, four array elements are uniformly distributed on a circular array, the array element distance d is half-wavelength of an expected signal, each antenna array element is an independent omnidirectional antenna, and satellite navigation signals and interference signals in different directions can be received at the same time.
See fig. 3. Uniform circular array four-channel array input signal xi(n), i ═ 1,2,3,4 by a delay of Z-1Calculating to realize time domain tapping, and snapshot data of each node of the time domain tapping and the corresponding weight coefficient wi,jAnd (n), multiplying the conjugate of (1, 2,3,4, j) by the conjugate of (1, 2,3,4, 5), and accumulating to obtain space-time two-dimensional beam synthesis array output data y (n).
In the embodiment, the conventional MVDR implementation algorithm is simplified, undistorted reception of the expected signal is guaranteed in the whole adaptive anti-interference iteration process, meanwhile, the DLMS idea is borrowed, the delay unit D is introduced, parallel calculation of the beam synthesis module and the weight iteration module is achieved, the adaptive iteration process is optimized again, and the problems of large calculation amount, large resource occupation and difficult hardware implementation of the conventional method are effectively solved. The invention has small data processing amount and good real-time property in the concrete realization process, is suitable for high-speed real-time signal processing and meets the requirements of engineering application.
Claims (6)
1. An anti-interference realization method of an adaptive array antenna is characterized by comprising the following steps: in the uniform circular array antenna with M antenna array elements, setting the antenna array element spacing as the half wavelength of the expected signal; each array element receives expected signals and interference signals from different directions, and M paths of digital signals are obtained after amplification, down conversion and analog-to-digital (AD) sampling; the data preprocessing module carries out N-order time domain tapping on the M paths of digital signals to obtain continuous space-time two-dimensional snapshot data, and meanwhile, corresponding space-time two-dimensional guide vectors are obtained according to expected signal directions provided by an upper computer; the minimum variance distortionless response MVDR algorithm simplification realization module calculates a guide vector residual matrix by utilizing a space-time two-dimensional guide vector, and simultaneously performs space-time two-dimensional beam synthesis and space-time two-dimensional weight iteration according to a built-in beam synthesis module and a weight iteration module by combining space-time two-dimensional snapshot data; the array output module converts the digital signals after beam forming into analog signals through a digital-to-analog DA converter, and the analog signals are up-converted and output to a rear-end processor through an up-conversion module.
2. The method for implementing interference rejection for an adaptive array antenna according to claim 1, wherein: the beam synthesis module directly weights according to the instantaneous snapshot data and the real-time weight to realize space-time two-dimensional beam synthesis, and the weight iteration module realizes iterative update of the weight coefficient by using the past snapshot data and the past beam synthesis data.
3. The method for implementing interference rejection for an adaptive array antenna according to claim 1, wherein: in the process of simplifying and realizing the minimum variance distortionless response MVDR algorithm, the product of a constraint space-time two-dimensional guide vector a and a space-time two-dimensional weighting vector w is always equal to 1, namely aHw (n) ═ 1, according to which the iteration parameter λ (n) ═ mua at the time n in the conventional implementation algorithm of the minimum variance distortionless response MVDR is simplifiedHa)-1(aHw(n)-2μaHR (n) w (n) -1) to obtain:
λ(n)＝(aHa)-1(2aHR(n)w(n))；
then, the formula w (n +1) ═ w (n) — μ (2r (n) w (n)) w (n) + λ (n) a is substituted into the weighting coefficient update formula of the conventional algorithm, so that: w (n +1) ═ w (n) -2 μ (I- (aa)H)/(aHa))R(n)w(n)；
Calculating R (n) ═ x (n) x from the autocorrelation matrixH(n), beam-forming data y (n) wH(n) x (n) to obtain:
w(n+1)＝w(n)-2μ(I-(aaH)/(aHa))x(n)conj(y(n))
h represents conjugate transpose, mu is iteration step size, I is unit matrix, R (n) is autocorrelation matrix, x is space-time two-dimensional snapshot data, and conj represents conjugate calculation.
4. The method for implementing interference rejection for an adaptive array antenna according to claim 3, wherein: adopting a delay strategy, introducing a delay unit D, and performing beam synthesisWhile obtaining array output data y (n), obtaining the weight required by the next iteration by using the delayed x (n-D) and y (n-D), so that the two processes of beam synthesis and weight iteration do not have a restriction relation in sequence, the weight iteration and the beam synthesis of the conventional serial operation are independent, and a new weight iteration formula is realized in parallel: w (n +1) ═ w (n) -2 μ (I- (aa)H)/(aHa) X (n-D) conj (y (n-D)) - (w) (n) -2 μ AB (n-D), wherein a ═ I- (aa) is definedH)/(aHa) For the steering vector residual matrix, B (n-D) ═ x (n-D) conj (y (n-D)) is the input-output delay correlation matrix.
5. The method for implementing interference rejection for an adaptive array antenna according to claim 3, wherein: the minimum variance distortionless response MVDR algorithm simplification realization module calculates a guide vector residual matrix A as I- (aa) according to a unit matrix I and a space-time two-dimensional guide vector a in a circular array antennaH)/(aHa)。
6. The method for implementing interference rejection for an adaptive array antenna according to claim 4, wherein: and the weight iteration module delays the space-time two-dimensional snapshot data x (n) and the array output data y (n) by D moments respectively to obtain an input-output delay correlation matrix B (n-D) ═ x (n-D) conj (y (n-D)), and then calculates the weight w (n +1) ═ w (n) -2 μ AB (n-D) at the moment n +1 by combining the iteration step size mu and the weight of the guide vector residual matrix A and the weight at the moment n.
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- 2018-02-11 CN CN201810143419.0A patent/CN108462521B/en active Active
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| Title |
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| 基于最小误码率准则的快速自适应波束成型算法;谢宁,王晖，陈金峰，周渊平;《中山大学学报（自然科学版）》;20100115;第43-47页 * |
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